Ontology highlight
ABSTRACT: Purpose
This study aims to integrate pancreatic cancer TCGA, GEO, and single-cell RNA-sequencing (scRNA-seq) datasets, and explore the potential prognostic markers and underlying mechanisms of the immune microenvironment of pancreatic cancer through bioinformatics methods, in vitro and in vivo assays.Methods
Expression data and clinicopathological data of pancreatic cancer TCGA, GEO (GSE131050), single cell sequencing (PAAD_CRA001160) dataset were downloaded. We used R/Bioconductor edgeR for differential expression analysis. ClusterProfiler was utilized to perform GO enrichment analysis on differentially expressed genes. The online software CIBERSORT was used to reanalyze the mRNA expression data of pancreatic cancer. CellRanger, RunPCA, FindNeighbors, FindClu
SUBMITTER: Yin L
PROVIDER: S-EPMC8828571 | biostudies-literature | 2021
REPOSITORIES: biostudies-literature